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Found 9 papers, 1 papers with code
Leveraging machine learning to enhance climate models: a review
Recent achievements in machine learning (Ml) have had a significant impact on various fields, including climate science.
Occlusion Aware Student Emotion Recognition based on Facial Action Unit Detection
Given that approximately half of science, technology, engineering, and mathematics (STEM) undergraduate students in U. S. colleges and universities leave by the end of the first year [15], it is crucial to improve the quality of classroom environments.
NewsClaims: A New Benchmark for Claim Detection from News with Attribute Knowledge
In this work, we present NewsClaims, a new benchmark for attribute-aware claim detection in the news domain.
Fine-grained Information Extraction from Biomedical Literature based on Knowledge-enriched Abstract Meaning Representation
In this paper, we propose a novel biomedical Information Extraction (IE) model to tackle these two challenges and extract scientific entities and events from English research papers.
COVID-19 Literature Knowledge Graph Construction and Drug Repurposing Report Generation
To combat COVID-19, both clinicians and scientists need to digest vast amounts of relevant biomedical knowledge in scientific literature to understand the disease mechanism and related biological functions.
Neural Generative Models for 3D Faces with Application in 3D Texture Free Face Recognition
Using heterogeneous depth cameras and 3D scanners in 3D face verification causes variations in the resolution of the 3D point clouds.
SemEval 2018 Task 6: Parsing Time Normalizations
This paper presents the outcomes of the Parsing Time Normalization shared task held within SemEval-2018.
Effect of Super Resolution on High Dimensional Features for Unsupervised Face Recognition in the Wild
Majority of the face recognition algorithms use query faces captured from uncontrolled, in the wild, environment.
Highly Scalable, Parallel and Distributed AdaBoost Algorithm using Light Weight Threads and Web Services on a Network of Multi-Core Machines
AdaBoost is an important algorithm in machine learning and is being widely used in object detection.
